Multiple Access Techniques for Intelligent and Multifunctional 6G: Tutorial, Survey, and Outlook

IF 23.2 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Proceedings of the IEEE Pub Date : 2024-06-18 DOI:10.1109/JPROC.2024.3409428
Bruno Clerckx;Yijie Mao;Zhaohui Yang;Mingzhe Chen;Ahmed Alkhateeb;Liang Liu;Min Qiu;Jinhong Yuan;Vincent W. S. Wong;Juan Montojo
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Abstract

Multiple access (MA) is a crucial part of any wireless system and refers to techniques that make use of the resource dimensions (e.g., time, frequency, power, antenna, code, and message) to serve multiple users/devices/machines/ services, ideally in the most efficient way. Given the increasing need of multifunctional wireless networks for integrated communications, sensing, localization, and computing, coupled with the surge of machine learning (ML)/artificial intelligence (AI) in wireless networks, MA techniques are expected to experience a paradigm shift in 6G and beyond. In this article, we provide a tutorial, survey, and outlook on past, emerging, and future MA techniques and pay particular attention to how wireless network intelligence and multifunctionality will lead to a rethinking of those techniques. This article starts with an overview of orthogonal, physical-layer multicasting, space domain, power domain (PD), rate-splitting, code-domain MAs, MAs in other domains, and random access (RA), and highlights the importance of conducting research in universal MA (UMA) to shrink instead of grow the knowledge tree of MA schemes by providing a unified understanding of MA schemes across all resource dimensions. It then jumps into rethinking MA schemes in the era of wireless network intelligence, covering AI for MA such as AI-empowered resource allocation, optimization, channel estimation, and receiver designs, for different MA schemes, and MA for AI such as federated learning (FL)/edge intelligence and over-the-air computation (AirComp). We then discuss MA for network multifunctionality and the interplay between MA and integrated sensing, localization, and communications, covering MA for joint sensing and communications, multimodal sensing-aided communications, multimodal sensing and digital twin-assisted communications, and communication-aided sensing/localization systems. We finish with studying MA for emerging intelligent applications such as semantic communications (SeComs), virtual reality (VR), and smart radio and reconfigurable intelligent surfaces (RISs), before presenting a roadmap toward 6G standardization. Throughout the text, we also point out numerous directions that are promising for future research.
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智能和多功能 6G 的多重接入技术:教程、调查和展望
多重接入(MA)是任何无线系统的重要组成部分,是指利用资源维度(如时间、频率、功率、天线、代码和信息)为多个用户/设备/机器/服务提供服务的技术,最好是以最有效的方式提供服务。鉴于多功能无线网络对集成通信、传感、定位和计算的需求与日俱增,再加上机器学习(ML)/人工智能(AI)在无线网络中的迅猛发展,预计 MA 技术将在 6G 及以后经历一次范式转变。在本文中,我们将对过去、新兴和未来的 MA 技术进行介绍、调查和展望,并特别关注无线网络的智能性和多功能性将如何导致对这些技术的重新思考。本文首先概述了正交、物理层组播、空间域、功率域 (PD)、速率分割、码域 MA、其他域中的 MA 以及随机接入 (RA),并强调了开展通用 MA (UMA) 研究的重要性,通过提供对所有资源维度 MA 方案的统一理解,缩小而不是扩大 MA 方案的知识树。然后,我们将跳转到对无线网络智能时代的无线宽带接入方案的重新思考,其中包括针对不同无线宽带接入方案的无线宽带接入人工智能,如人工智能驱动的资源分配、优化、信道估计和接收器设计,以及针对人工智能的无线宽带接入,如联合学习(FL)/边缘智能和空中计算(AirComp)。然后,我们将讨论用于网络多功能性的人工智能,以及人工智能与综合传感、定位和通信之间的相互作用,包括用于联合传感和通信、多模态传感辅助通信、多模态传感和数字孪生辅助通信,以及通信辅助传感/定位系统的人工智能。最后,我们研究了用于新兴智能应用的 MA,如语义通信 (SeComs)、虚拟现实 (VR)、智能无线电和可重构智能表面 (RIS),然后提出了实现 6G 标准化的路线图。在全文中,我们还指出了许多很有希望的未来研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Proceedings of the IEEE
Proceedings of the IEEE 工程技术-工程:电子与电气
CiteScore
46.40
自引率
1.00%
发文量
160
审稿时长
3-8 weeks
期刊介绍: Proceedings of the IEEE is the leading journal to provide in-depth review, survey, and tutorial coverage of the technical developments in electronics, electrical and computer engineering, and computer science. Consistently ranked as one of the top journals by Impact Factor, Article Influence Score and more, the journal serves as a trusted resource for engineers around the world.
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